DESCRIPTION: Glioblastoma multiforme (GBM) is the most common, aggressive, and deadly form of brain cancer GBM spreads rapidly and diffusely via distinct invasive processes, making it essential to investigate phenomena occurring at the tumor margins. And given the number of independent genomic mutations associated with GBM, it is critical to develop biomimetic tissue engineering approaches to directly study patient-derived biospecimens rather than generic cell lines. A major bottleneck in the field is that it remains unclear how combinations of biophysical and biomolecular signals that exist in close spatial and temporal order across the GBM tumor affect malignant phenotype and response to therapy. Spatially-patterned biomaterials capable of replicating regulatory elements of the native tumor microenvironment such as the margins are essential. We have developed a microfluidic forming technique to create libraries of optically-translucent engineered glioma biomaterials containing overlapping patterns of cell, matrix, and biomolecular cues inspired by the GBM margins. We are able to map cell response as a function of local microenvironment via multiplexed analyses of cells from discrete sub-regions of the EG via transcriptomic, secretomic, and imaging metrics. While successful for resolving clinically-relevant phenomena using immortalized cell lines, there is an acute clinical need for point-of-care tools able to gather similar information from patient-derived biospecimens. The primary objective of this application is to demonstrate a biomimetic tissue engineering approach to investigate mechanisms underlying phenotype using patient-derived biospecimens ex vivo. Aim 1 will dissect how overlapping patterns of tumor margin-inspired signals shape malignant phenotype. Aim 2 will define the contribution of perivascular signals on invasive phenotype. Aim 3 will employ engineered gliomas to resolve discordances between orthotopic and heterotopic xenograft tumors via quantitative benchmarking against clinical phenotype. Engineered glioma biomaterials offer the potential for insight regarding spatial and temporal aspects of the GBM microenvironment in ways not possible with current experimental approaches. Our use of a scalable microfluidic platform as well as multiplexed assessment of GBM cells via conventional and next generation molecular analysis tools greatly reduces the size of the required patient biospecimen, accelerates the speed of analysis, and yet preserves the capability of interrogating rare cell subpopulations such as glioma cancer stem cells. Engineered glioma biomaterials have the potential to b